New ScyllaDB Release is a DynamoDB Alternative That Scales Faster and Costs 50% Less

ScyllaDB Inc. announced the availability of ScyllaDB X Cloud, a truly elastic database that helps teams achieve predictable performance at scale – without overprovisioning. Database capacity can be increased rapidly and precisely when required, then scaled back as soon as the surge subsides.For example, ScyllaDB can scale from 100K to 2M operations per second in just minutes, with consistent single-digit millisecond P99 latency even during scaling, backup, and failure recovery. As a result, teams don’t need to wastefully overprepare for potential peaks or suffer suboptimal performance due to traditional scaling lag.

The new release extends elastic scaling to use cases that involve advanced ScyllaDB capabilities such as Change Data Capture, Materialized Views, and Secondary Indexes. Most notably, it extends this capability to ScyllaDB’s DynamoDB-compatible API (Alternator). Although ScyllaDB was created as an Apache Cassandra alternative, it has become increasingly popular as a DynamoDB alternative over the past two years. Teams have been migrating from DynamoDB to ScyllaDB to reduce costs, support multicloud or cloud migration initiatives, and avoid DynamoDB technical limitations such as item size limits. Now, teams can also increase/reduce capacity faster than DynamoDB.

Additionally, ScyllaDB now guarantees that ScyllaDB X Cloud costs are 50% of DynamoDB costs (or less). ScyllaDB’s inherent efficiency comes from a close-to-the-metal design, features such as dictionary-based compression and file-based streaming, and ongoing performance optimizations.

“ScyllaDB supported cross-cloud deployments, required a manageable number of servers, and offered competitive costs. Best of all, its API was DynamoDB-compatible, meaning we could migrate with minimal code changes. In fact, a single engineer implemented the necessary modifications in just a few days,” said According to Todd Coleman, chief architect and technical co-founder, Yieldmo.

“DynamoDB’s item size limitation forced multiple steps: we had to split the data into multiple records, write it, and then fetch it again. All of this logic ended up adding compute overhead. So, we migrated to ScyllaDB because these limitations don’t exist there,” said Prem Kumar Patturaj, senior engineering manager, Freshworks.